1 citations · 1 across the 2 of their papers we have counts for
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Dataset Reset Policy Optimization for RLHF
Jonathan D. Chang, Wenhao Zhan, Owen Oertell +4
Reinforcement Learning (RL) from Human Preference-based feedback is a popular paradigm for fine-tuning generative models, which has produced impressive models such as GPT-4 and Cla…
Provable Interactive Learning with Hindsight Instruction Feedback
Dipendra Misra, Aldo Pacchiano, Robert E. Schapire
We study interactive learning in a setting where the agent has to generate a response (e.g., an action or trajectory) given a context and an instruction. In contrast, to typical ap…
Policy Improvement using Language Feedback Models
Victor Zhong, Dipendra Misra, Xingdi Yuan +1
We introduce Language Feedback Models (LFMs) that identify desirable behaviour - actions that help achieve tasks specified in the instruction - for imitation learning in instructio…
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan T. Ash, Dipendra Misra
Transformer-based Large Language Models (LLMs) have become a fixture in modern machine learning. Correspondingly, significant resources are allocated towards research that aims to…